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In this research, an export coefficient based inexact fuzzy bi-level multi-objective programming (EC-IFBLMOP) model was developed through integrating export coefficient model (ECM), interval parameter programming (IPP) and fuzzy parameter programming (FPP) within a bi-level multi-objective programming framework. The proposed EC-IFBLMOP model can effectively deal with the multiple uncertainties expressed as discrete intervals and fuzzy membership functions. Also, the complexities in agricultural systems, such as the cooperation and gaming relationship between the decision makers at different levels, can be fully considered in the model. The developed model was then applied to identify the optimal land use patterns and BMP implementing levels for agricultural nonpoint source (NPS) pollution management in a subcatchment in the upper stream watershed of the Miyun Reservoir in north China. The results of the model showed that the desired optimal land use patterns and implementing levels of best management of practices (BMPs) would be obtained. It is the gaming result between the upper- and lower-level decision makers, when the allowable discharge amounts of NPS pollutants were limited. Moreover, results corresponding to different decision scenarios could provide a set of decision alternatives for the upper- and lower-level decision makers to identify the most appropriate management strategy. The model has a good applicability and can be effectively utilized for agricultural NPS pollution management. [ABSTRACT FROM AUTHOR]

Abstract: In this study, a feasibility based inexact fuzzy programming approach (FBIFP) was developed and applied to the planning of a regional electric power generation system (REPGS). As an extension of existing interval linear programming and fuzzy linear programming, FBIFP could tackle uncertainties expressed as intervals, fuzzy sets as well as their combination in both of the objective function and constraints. Through introducing the index of feasibility degree, FBIFP could be used to facilitate the efficient reflection of constraint violation, and thus allow decision makers to have a complete view of the relationships between uncertain inputs and the related solutions. A hypothetic regional electric power generation system was provided for demonstrating applicability of the developed model. Useful solutions for the planning of REPGS were generated. Interval solutions under different feasibility degrees were obtained. They could be used for helping decision makers identify desired alternatives under various reliability risks of the system. The solutions could also help identify optimal patterns for energy resources allocation, electricity generation and facility capacity expansion with a minimized system cost. Tradeoffs between system costs and system security could be successfully addressed through the analysis of the feasibility degrees of constraints, i.e., a higher feasibility degree would correspond to a higher system cost, while a lower system cost would run into a higher risk of potential instability of the study system. [Copyright &y& Elsevier]